Machine Learning

Autoencoder Asset Pricing Models

We propose a new latent factor conditional asset pricing model, which delivers out-of-sample pricing errors that are far smaller (and generally insignificant) compared to other leading factor models.

ESG Investing

Hedging Climate Change News

We propose and implement a procedure to dynamically hedge climate change risk and discuss multiple directions for future research on financial approaches to managing climate risk.

Fixed Income

Give Credit Where Credit Is Due: What Explains Corporate Bond Returns?

We examine the risk and returns of U.S. corporate bond indices using a set of economically-motivated factors and find that options markets explain a great deal of credit returns.

Alternative Investing

Trends Everywhere

We provide new out-of-sample evidence on trend-following investing by studying its performance for 82 securities not previously examined and 16 long-short equity factors.

Factor/Style Investing

Factor Momentum Everywhere

Can individual factors be reliably timed based on their recent performance? This study of 65 widely-studied, characteristic-based equity factors aims to find out.


Forecasting the Distribution of Option Returns

We propose a method for constructing conditional option return distributions.

Market Risk and Efficiency

A Framework for Identifying Accounting Characteristics for Asset Pricing Models, with an Evaluation of Book-to-Price

We provide a framework for identifying accounting numbers that indicate risk and expected return.

Alternative Investing

Optimal Currency Hedging for International Equity Portfolios

We explore currency exposures in international equity portfolios by decomposing the optimal currency portfolio into a “hedge portfolio,” which minimizes equity volatility, and an “alpha seeking portfolio” based on the well-documented currency styles of value, momentum and carry.


Characteristics Are Covariances: A Unified Model of Risk and Return

We propose a new modeling approach for the cross section of returns that helps determine whether excess returns to factors are driven by compensation for risk, or an anomaly effect.

Machine Learning

Empirical Asset Pricing via Machine Learning

We show how the field of machine learning can be used to empirically investigate asset premia including momentum, liquidity, and volatility.